Bipolar Ionic Diode with a Transformable Polyelectrolyte Network for High-Efficiency Ion Transport and Enhanced Sensitivity in Fluorescence-Based Heavy Metal Ion Detection
Bibliographic record
Abstract
Recent studies on ionic diodes for ion transport regulation have shown promising functions with high rectification ratios. However, typical ionic diodes face challenges in attaining high output efficiency and ion flux due to their requirement of nanoscale dimensions for ion selectivity. In this article, we introduce a novel bipolar ionic diode constructed through the combined assembly of nanoparticles and a transformable polyelectrolyte network. Experimental and numerical studies were conducted to characterize and optimize the fabrication parameters, resulting in a remarkable rectification ratio exceeding 1000. The presented ionic diode possesses the unique capability to automatically transform from a dense to a loose structure in response to an applied potential bias. This feature enables high output efficiency and rapid ion accumulation. Leveraging these characteristics, we developed a fluorescence-based sensor with ultrahigh sensitivity for nickel ions, achieving a detection limit of 1 nM with a minimal sample volume of 50 μL─an improvement of 2 orders of magnitude over conventional bulk solutions with the same fluorescence indicator. This ionic diode demonstrates exceptional ability and flexibility in high-efficiency ion transport, positioning itself as a promising platform with broad applications for enhancing sensitivity in various fluorescence-based sensing applications within aqueous environments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".